INSIGHT: Expect a drop in the ‘check-the-box’ approach to AML in 2026

AS we enter 2026, AML practitioners stand at a pivotal crossroads.

The past year has brought notable regulatory shifts, a surge in criminal sophistication powered by advanced technologies, and a rapid evolution in AI. These changes have set the stage for a new era in financial crime prevention, one that demands a strategic recalibration of priorities and resources.

This convergence of factors has set the stage for us to supercharge the capabilities of investigators and empower them to get back to focusing on their core mission: detect and deter suspicious activity and pass along intelligence to law enforcement.

Regulatory Changes

Throughout the past year, we’ve seen a notable shift in tone from both government and regulators, particularly in the U.S.

A confluence of events – from the introduction of the Streamline Act in the Senate and new SAR FAQs from FinCEN to the OCC’s decision to end money laundering risk system data collection for community banks and a pause on the Corporate Transparency Act (CTA) and the Foreign Corrupt Practices Act (FCPA) – signal a different regulatory approach.

While some institutions have welcomed the prospect of reduced regulatory burden, many in the industry remain cautious about the implications of these changes.

Still, the new regulatory approach signals that regulators may be looking to scale back “check-the-box” exercises in favor of guidance that gets back to the core of AML programs – identifying suspicious activity, sharing actionable intelligence with law enforcement, and removing criminals from the financial system. 

Evolving criminal threats

The complexity and scale of financial crime continue to reach new heights, fueled by advances in AI. Deepfakes, synthetic identities, and elaborate fraud schemes have proliferated, as AI tools are enabling criminal organizations to operate with the sophistication of diversified businesses.

The convergence of proceeds from drug trafficking, human trafficking, and various scams has enabled these actors to maximize illicit gains while evading detection.

The explosion in data—from money movement to network associations—has made it increasingly difficult for investigators to identify the critical threads that unravel complex criminal networks. The growing professionalization and sophistication of criminal enterprises mean that a single overlooked data point can be the gateway to exposing a much larger scheme. 

Criminal networks take tried and true financial crime playbooks from institution to institution, exploiting information silos and a lack of collaboration to avoid detection. We can no longer afford to fight financial crime in isolation.

Today’s financial crime threats require great collaboration – between financial institutions, the public and private sector, and even between industries. As an industry, embracing solutions that use the power of consortium data and collective intelligence can help financial institutions uncover criminals hiding in plain sight, with risk insights that no institution could discover on their own.

As the threat landscape evolves, AML teams must remain vigilant and leverage advanced analytical tools to stay ahead.

A new frontier in AI

The age of AI has moved from experimentation to implementation as financial institutions embrace the technology to automate and streamline repetitive, manual activities across their organization. Generative AI, once a buzzword, has matured into a practical tool for AML operations. Yet the real breakthrough has been last year’s emergence of agentic AI—systems capable of reasoning, planning, executing multi-step tasks, and making recommendations with minimal human oversight.

Agentic AI has the potential to revolutionize AML investigations and workflows. Financial institutions are tasked with a compounding number of challenges, from navigating changing regulatory requirements to managing an increasing number of alerts and false positives. Agentic AI offers a reprieve from repetitive, high-volume compliance processes, with the ability to handle complex workflows like sanctions screening and enhanced due diligence reviews while requiring minimal human oversight. 

This technology benefits institutions of all sizes, enabling large teams to redeploy resources to higher-value work and empowering smaller teams to expand their capabilities. It is increasingly clear that AI is not optional—it is essential for keeping pace with evolving threats in financial crime.

Advice for practitioners in 2026

Too often, investigators are bogged down by inefficient workflows, excessive documentation, and fragmented systems that distract from the core mission. In 2026, the priority must be to streamline processes, eliminate redundant tasks, and leverage technology to automate routine activities such as sanctions screening, enhanced due diligence reviews, regulatory report filing and investigations.

Empowering investigators to concentrate on important investigations rather than operational tasks requires a commitment to efficiency and a willingness to challenge organizational inertia. Routine, level-one tasks should be automated, freeing skilled professionals to apply their judgment and expertise where it matters most. The workforce will evolve, but the need for talented investigators will remain a cornerstone of effective AML programs.

The challenges ahead are daunting, but with the right tools, mindset, and commitment to efficiency, AML teams can continue to safeguard their institutions and wider financial system. The future of financial crime prevention depends on our ability to adapt, innovate, and work together.

Let us seize the opportunity to redefine AML for a new era—one where complexity is minimized, impact is maximized, and criminals are decisively removed from the financial system.